MEDISIS Fishing Effort Map
Stephanie Hopkins
<<<<<<< HEAD15 March, 2024
=======07 March, 2024
>>>>>>> 47bed0620551ce537ae199460bc472d176dbb760Load the european coast line and grid
This will serve as a base map for all other plots. You can actually use the rworldmap and rworldxtra libraries if you do not yet have a shape file.
shapes_subfolder <- "Data/Shape.files/"
GDL_extension <- "Extra/carto/shapefile/Europe_coastline_shapefile/"
GDL <- read_sf(paste(path, shapes_subfolder, GDL_extension, "GDL.shp", sep = ""))
plot(GDL)
# NOTE: Grid extent should be 3, 6, 42.00, 43.55
GDL_crop <- st_crop(GDL, xmin=2.95, xmax=6.05, ymin=41.95, ymax=43.6)
plot(GDL_crop)
grid <- read_sf(paste(path, shapes_subfolder, "Grid/grid.shp", sep = ""))
plot(grid)
p <- ggplot() +
geom_sf(data=GDL_crop, color = alpha("grey", 1/2), size = 0.7, fill = 'darkgrey', alpha = .3) +
geom_sf(data = grid, color = "grey")
p
rm(GDL)Load Spatial Closures
FRA <- read_sf(paste(path, shapes_subfolder, "FRA/FRAs_WGS84.shp", sep = ""))
FRA <- FRA[1,]
p + geom_sf(data = FRA, fill = 'yellowgreen', alpha = 0.3)
#---------------------------------------------------------------------------
NewFRA_regulation <- read_sf(paste(path, shapes_subfolder, "NewFRA_regulation/boxPaca_polygon_4326.shp", sep = ""))
p + geom_sf(data = NewFRA_regulation, fill = 'yellowgreen', alpha = 0.3)
#---------------------------------------------------------------------------
zone_90_100_simplified <- read_sf(paste(path, shapes_subfolder, "zone_90_100_simplified/zone_90_100_simplifiee_Visvalingram_0_05_deg_accroche_dm_polygon_4326.shp", sep = ""))
p + geom_sf(data = zone_90_100_simplified, fill = 'yellowgreen', alpha = 0.3)
#---------------------------------------------------------------------------
Offshore_closure_z1 <- read_sf(paste(path, shapes_subfolder, "Offshore_closures/zone1.shp", sep = ""))
Offshore_closure_z2 <- read_sf(paste(path, shapes_subfolder, "Offshore_closures/zone2.shp", sep = ""))
Offshore_closure_z3 <- read_sf(paste(path, shapes_subfolder, "Offshore_closures/zone3.shp", sep = ""))
# Group the Offshore_closures into one file
Offshore_permanent_spdf <- rbind(Offshore_closure_z1, Offshore_closure_z2, Offshore_closure_z3)
p + geom_sf(data = Offshore_permanent_spdf, fill = 'yellowgreen', alpha = 0.3)
#---------------------------------------------------------------------------
Offshore_closure_seasonal <- read_sf(paste(path, shapes_subfolder, "Offshore_closures/Offshore_closure_seasonal_final.shp", sep = ""))
p + geom_sf(data = Offshore_closure_seasonal, fill = 'yellowgreen', alpha = 0.3)
Create spatial points for port of calls
Because we are not interested in squares use the actual gps coords. These were pulled from:
<<<<<<< HEADFor Grau du Roi, Sète, and Marseille:
=======For Grand du Roi, Sète, and Marseille:
>>>>>>> 47bed0620551ce537ae199460bc472d176dbb760https://latitude.to/map/fr/france/cities/
For all others:
https://www.toutendroit.com/en/article-le-grau-d-agde-1884412/ https://www.gps-latitude-longitude.com/gps-coordinates-of-port-la-nouvelle https://www.countrycoordinate.com/city-port-de-bouc-france/
Abbreviation <- c("GST", "XST", "CST", "GPV", "CMT", "XMA")
<<<<<<< HEAD
Name <- c("Grau-du-Roi", "Sete", "Le-Grau-d'Adge", "Port-la-Nouvelle", "Port-de-Bouc", "Marseille")
=======
Name <- c("Grand-du-Roi", "Sete", "Le-Grau-d'Adge", "Port-la-Nouvelle", "Port-de-Bouc", "Marseille")
>>>>>>> 47bed0620551ce537ae199460bc472d176dbb760
cell <- c("La43.5Lo4.1", "La43.35Lo3.6", "La43.25Lo3.4", "La43.0Lo3.05", "La43.4Lo4.9", "La43.25Lo5.35")
longitude <- c(4.13559, 3.69278, 3.447424, 3.043916, 4.985931, 5.38107)
latitude <- c(43.53881, 43.4028, 43.282701, 43.021342, 43.405449, 43.29695)
Ports <- data.frame(Abbreviation, Name, cell, longitude, latitude)
head(Ports)
# convert Ports to an spatial points data.frame
Ports.wgs84 <- st_as_sf(Ports,coords = c("longitude", "latitude"), crs = st_crs(4326))
GPV.wgs84 <- subset(Ports.wgs84, Name == "Port-la-Nouvelle")
CST.wgs84 <- subset(Ports.wgs84, Name == "Le-Grau-d'Adge")
XST.wgs84 <- subset(Ports.wgs84, Name == "Sete")
<<<<<<< HEAD
GST.wgs84 <- subset(Ports.wgs84, Name == "Grau-du-Roi")
=======
GST.wgs84 <- subset(Ports.wgs84, Name == "Grand-du-Roi")
>>>>>>> 47bed0620551ce537ae199460bc472d176dbb760
CMT.wgs84 <- subset(Ports.wgs84, Name == "Port-de-Bouc")
XMA.wgs84 <- subset(Ports.wgs84, Name == "Marseille")Create a custom theme for the map legends
text_theme <- theme(axis.title = element_blank(), axis.text.y = element_text(margin=margin(t=0,r=0,b=0,l=0), size = 15), axis.text.x.bottom = element_text(margin=margin(t=0,r=0,b=0,l=0), size = 15), strip.text = element_text(size=15), panel.spacing = unit(0.35, "cm"))Create custom scales
For the spatial closure legend.
cols <- c("#003366" = str_wrap("Seasonal Offshore Extensions Applies to Gears: OTB, OTT, GNS, and LLS Seasonally (Oct-Dec) or allYear", 28),
"#b2182b" = str_wrap("Offshore Permanent Closures Applies to Gears: OTB, OTT, GNS, LLS allYear", 28),
"#FF33FF" = str_wrap("90-100 Isobaths Closures Applies to Gears: OTB and OTT Seasonally (Sept-Apr) or allYear", 28),
"#614B00" = str_wrap("Northward Expansion of FRA Applies to Gears: OTB and OTT Seasonally (Nov-Apr) or allYear", 28))
cols2 <- ("#614B00" = str_wrap("Original Fishing Restricted Area [FRA] Boundaries Applies to Gears: OTB and OTT allYear", 28))For the figure without a spatial closure legend.
cols3 <- c("Offshore_closure_seasonal" = "#003366",
"Offshore_permanent_spdf" = "#b2182b",
"zone_90_100_simplified" = "#FF33FF",
"NewFRA_regulation" = "#614B00")
cols4 <- c("FRA" = "#614B00")Reorder the groups that we are interested in
EffortMetierZonesPLUS.correct2.2024 <-
fread(file = paste(path,'Data/EffortMetierZonesPLUS.correct2.csv', sep = ''),
sep = ",")
EffortMetierZonesPLUS.correct_reorder <-
EffortMetierZonesPLUS.correct2.2024 %>% mutate(
SceName_short =
recode_factor(SceName,
"StatusQuo"= "a",
"Trawler_30_Red"= "b",
"AllGears_30_Red" = "c",
"Trawler_40_Red" = "d",
"AllGears_40_Red"= "e",
"Trawler_50_Red"= "f",
"AllGears_50_Red"= "g",
"Trawler_10_20_30"= "h",
"AllGears_10_20_30"= "i",
"Trawler_10_17.5_25_32.5_40"= "j",
"AllGears_10_17.5_25_32.5_40"= "k",
"Trawler_10_20_30_40_50"= "l",
"AllGears_10_20_30_40_50"= "m",
"Original_FRA_allYear"= "n",
"Northward_Expansion_of_FRA_Season"= "o",
"Northward_Expansion_of_FRA_allYear" = "p",
"90-100_Isobaths_Closure_Season"= "q",
"90-100_Isobaths_Closure_allYear"= "r",
"Offshore_Closures_Season"= "s",
"Offshore_Closures_allYear"= "t",
"Northward_Expansion_of_FRA_90-100m_Offshore_Closures_Combined"= "u",
"Northward_Expansion_of_FRA_Offshore_Closures_Combined" = "v",
"Northward_Expansion_of_FRA_90-100m_Offshore_allYear_Closures_Combined" = "w",
"Northward_Expansion_of_FRA_Offshore_allYear_Closures_Combined" = "x",
"Combined_Red_10_17.5-40_Northward_Expansion_of_FRA_90-100m_Offshore_Closures"= "y",
"Combined_Red_10_17.5-40_Northward_Expansion_of_FRA_Offshore_Closures"= "z",
"Combined_Red_10_17.5-40_Northward_Expansion_of_FRA_90-100m_Offshore_Closures_allGears"= "aa",
"Combined_Red_10_17.5-40_Northward_Expansion_of_FRA_Offshore_Closures_allGears"= "bb"
))
# View(EffortMetierZonesPLUS.correct_reorder)Create a Combined Effort map by Scenario and Year
Notes, it was decided to create two quantile scales to compare canyon and continental shelf outcomes. Subset by cell id.
Create a Custom Secondary Palette
Required for the scale_fill_manual function.
Canyon_pal <- c("#f3e6f3","#e8cce8","#d199d1","#b966b9","#a233a2","#971997","#8b008b")
pie(rep(1, 7), col = Canyon_pal)
Apendix F, Figs. F.2 - F.6
Note: You will need to move the legends around to fit everything.
Continental_cells <-
read.csv(file = paste(path, 'Data/Continental_cells.csv', sep = ''))
Continental_cells <- unique(Continental_cells$x)
Canyon_cells <-
read.csv(paste(path, 'Data/Canyon_cells.csv', sep = ''))
Canyon_cells <- unique(Canyon_cells$x)
EffortAggregatedZones <- aggregate(NewEffort ~ cell + longitude + latitude + YEAR +
SceName_short + SceName, data =
EffortMetierZonesPLUS.correct_reorder, FUN = sum)
EffortAggregatedZones$Pop_zone <- NA
EffortAggregated_plateau <- subset(EffortAggregatedZones, cell %in% Continental_cells)
EffortAggregated_plateau$Pop_zone <- 1
EffortAggregated_canyon <- subset(EffortAggregatedZones, cell %in% Canyon_cells)
EffortAggregated_canyon$Pop_zone <- 2
EffortAggregatedZones2 <- rbind(EffortAggregated_plateau, EffortAggregated_canyon)
unique(is.na(EffortAggregatedZones2))
unique(EffortAggregatedZones2$NewEffort)
zone_effort_plots = F
if (zone_effort_plots == FALSE){
for (s in unique(EffortAggregatedZones2$SceName)){
effort_scen_subset <- EffortAggregatedZones2[EffortAggregatedZones2$SceName == s, ]
print(s)
Map_label <- unique(effort_scen_subset$SceName)
# Shift so that longitude corresponds to the center of the ISIS-Fish cell
effort_scen_subset$longitude <- effort_scen_subset$longitude + 0.025
# Shift so that latitude corresponds to the center of the ISIS-Fish cell
effort_scen_subset$latitude <- effort_scen_subset$latitude + 0.025
# Create a sf object
effort_scen_subset_wgs84 <- st_as_sf(effort_scen_subset,
coords = c("longitude", "latitude"),
crs = st_crs(4326))
# Create gridded polygon values
effort_scen_subset_stars <- st_rasterize(effort_scen_subset_wgs84,
st_as_stars(st_bbox(grid),
values = NA_real_,
dx = 0.05,
dy = 0.05))
effort_scen_subset_sf <- st_as_sf(effort_scen_subset_stars)
effort_scen_subset_sf_shelf <- subset(effort_scen_subset_sf,
Pop_zone == 1)
# get quantile breaks. Add .00001 offset to catch the lowest value
breaks_qt_shelf <-
classIntervals(c(min(effort_scen_subset_sf_shelf$NewEffort) -
.00001, effort_scen_subset_sf_shelf$NewEffort), n = 7,
style = "quantile")
effort_scen_subset_sf_shelf <-
mutate(effort_scen_subset_sf_shelf, Effort.cut_shelf =
cut(NewEffort, breaks_qt_shelf$brks))
effort_scen_subset_sf_canyon <- subset(effort_scen_subset_sf,
Pop_zone == 2)
# get quantile breaks. Add .00001 offset to catch the lowest value
breaks_qt_canyon <-
classIntervals(c(min(effort_scen_subset_sf_canyon$NewEffort) -
.00001, effort_scen_subset_sf_canyon$NewEffort),
n = 7, style = "quantile")
effort_scen_subset_sf_canyon <-
mutate(effort_scen_subset_sf_canyon, Effort.cut_canyon =
cut(NewEffort, breaks_qt_canyon$brks))
e.m.1 <- ggplot() +
geom_sf(data = grid, color = "grey") +
geom_sf(data = effort_scen_subset_sf_shelf,
aes(fill = Effort.cut_shelf),
color = "transparent",
alpha = 0.8) +
scale_fill_brewer(name = "Zone 1",
palette = "Blues") +
guides(fill=guide_legend(order = 1))+
new_scale_fill() +
geom_sf(data = effort_scen_subset_sf_canyon,
aes(fill = Effort.cut_canyon),
color = "transparent", alpha = 0.8) +
scale_fill_manual(name = "Zone 2",
values = Canyon_pal) +
theme_bw()+
theme(legend.title = element_text(size = 14), legend.title.align = 0,
legend.text = element_text(size = 12), legend.spacing = unit(0.001, 'cm'),
legend.position="right", legend.box = "horizontal") +
text_theme
e.m.1
e.m.1.legend <- gtable_filter(ggplot_gtable(ggplot_build(e.m.1)), "guide-box")
e.m.2 <- ggplot() +
geom_sf(data = grid,
color = "grey") +
geom_sf(data = zone_90_100_simplified,
aes(color = "#FF33FF"),
fill = "transparent",
linewidth = 0.5) +
geom_sf_pattern(data = FRA,
aes(pattern_fill = "#614B00"),
pattern_fill2 = "transparent",
pattern_colour = "transparent",
color = "#614B00",
fill = "transparent",
pattern_aspect_ratio = 1.8,
linewidth = 0.5,
pattern_spacing = 0.01) +
geom_sf(data = NewFRA_regulation,
aes(color = "#614B00"),
fill = "transparent",
linewidth = 0.5) +
geom_sf(data = Offshore_closure_seasonal,
aes(color = "#003366"),
fill = "transparent",
linewidth = 0.25) +
geom_sf(data = Offshore_permanent_spdf,
aes(color = "#b2182b"),
fill = "transparent",
linewidth = 0.5) +
scale_color_identity(name = "Closure Measures",
labels = cols,
guide = guide_legend("color")) +
scale_pattern_fill_identity(name = element_blank(),
labels = cols2,
guide = guide_legend("pattern_fill"))+
guides(color = guide_legend(order = 1),
pattern_fill = guide_legend(order = 2)) +
theme_bw() +
theme(legend.title = element_blank(), legend.text = element_text(size = 12),
legend.margin = unit(0.00, 'cm'), legend.spacing = unit(1, 'cm'),
legend.position="left", legend.box = "vertical", legend.key.height =
unit(1.52, 'cm'), legend.key.width = unit(1.5, 'cm')) +
text_theme
e.m.2
e.m.2.legend <- gtable_filter(ggplot_gtable(ggplot_build(e.m.2)), "guide-box")
e.m.no.legend <-ggplot() +
geom_sf(data = grid,
color = "grey") +
geom_sf(data = effort_scen_subset_sf_shelf,
aes(fill = Effort.cut_shelf),
color = "transparent",
alpha = 0.8) +
scale_fill_brewer(effort_scen_subset_sf_shelf,
name = "Zone 1",
palette = "Blues") +
guides(fill=guide_legend(order = 1))+
new_scale_fill() +
geom_sf(data = effort_scen_subset_sf_canyon,
aes(fill = Effort.cut_canyon),
color = "transparent",
alpha = 0.8) +
scale_fill_manual(effort_scen_subset_sf_canyon,
name = "Zone 2",
values = Canyon_pal) +
geom_sf(data = grid,
color = "grey") +
geom_sf(data = zone_90_100_simplified,
aes(color = "#FF33FF"),
fill = "transparent",
linewidth = 0.5) +
geom_sf_pattern(data = FRA,
aes(pattern_fill = "#614B00"),
pattern_fill2 = "transparent",
pattern_colour = "transparent",
color = "#614B00",
fill = "transparent",
pattern_aspect_ratio = 1.8,
linewidth = 0.5,
pattern_spacing = 0.01) +
geom_sf(data = NewFRA_regulation,
aes(color = "#614B00"),
fill = "transparent",
linewidth = 0.5) +
geom_sf(data = Offshore_closure_seasonal,
aes(color = "#003366"),
fill = "transparent",
linewidth = 0.25) +
geom_sf(data = Offshore_permanent_spdf,
aes(color = "#b2182b"),
fill = "transparent",
linewidth = 0.5) +
scale_color_identity(name = "Closure Measures",
labels = cols,
guide = guide_legend("color")) +
scale_pattern_fill_identity(name = element_blank(),
labels = cols2,
guide = guide_legend("pattern_fill"))+
geom_sf(data = GDL_crop,
color = "#ae8f60",
size = 0.7,
fill = "#E1C699") +
geom_sf(data = GPV.wgs84, size = 1) +
geom_sf_text(data = GPV.wgs84,
aes(label = Abbreviation),
size = 3.5,
color = "black",
nudge_x = -0.02,
nudge_y = 0.04) +
geom_sf(data = CST.wgs84, size = 1) +
geom_sf_text(data = CST.wgs84,
aes(label = paste0(Name, " (", Abbreviation, ")", sep = '')),
size = 3.5,
color = "black",
nudge_x = -0.18,
nudge_y = 0.04) +
geom_sf(data = XST.wgs84, size = 1) +
geom_sf_text(data = XST.wgs84,
aes(label = paste0(Name, " (", Abbreviation, ")", sep = '')),
size = 3.5,
color = "black",
nudge_x = -0.10,
nudge_y = 0.04) +
geom_sf(data = GST.wgs84, size = 1) +
geom_sf_text(data = GST.wgs84,
aes(label = paste0(Name, " (", Abbreviation, ")", sep = '')),
size = 3.5,
color = "black",
nudge_x = -0.01,
nudge_y = 0.04) +
geom_sf(data = CMT.wgs84, size = 1) +
geom_sf_text(data = CMT.wgs84,
aes(label = paste0(Name, " (", Abbreviation, ")", sep = '')),
size = 3.5,
color = "black",
nudge_x = 0.05,
nudge_y = 0.04) +
geom_sf(data = XMA.wgs84, size = 1) +
geom_sf_text(data = XMA.wgs84 ,
aes(label = paste0(Name, " (", Abbreviation, ")", sep = '')),
size = 3.5,
color = "black",
nudge_x = 0.20,
nudge_y = 0.04) +
annotation_scale(location = "br",
pad_x = unit(0.85, "cm"),
pad_y = unit(0.5, "cm"),
text_cex = 1,
tick_height = 0.9)+
annotation_north_arrow(location = "tl",
which_north = "true",
height = unit(1, "cm"),
width = unit(1, "cm"),
pad_x = unit(1.25, "cm"),
pad_y = unit(0.75, "cm")) +
theme_bw()+
theme(axis.title = element_blank(),legend.position = "none") +
text_theme
plotlegends <- arrangeGrob(e.m.1.legend, e.m.2.legend, heights = c(0.45, 0.55))
plotNew <- arrangeGrob(e.m.no.legend, plotlegends, widths = c(0.67,0.33))
plotNew.ggplot <- ggplotify::as.ggplot(plotNew)
print(plotNew.ggplot)
file.name <- paste("2024_Effort_Re-distribution- ", Map_label, sep = '')
ggsave2(filename=paste(file.name,".pdf",sep=''),plot=plotNew.ggplot,device="pdf",
path=paste(path,"Figures/",sep=""), dpi=1200, width = 29.7, height=17,
unit="cm",
limitsize = FALSE)
}
}
